OCR Text |
Show '00 s* 5 5 2 > 3 2 100 - 30 - 50 - 40 - 2n "i Bagasse. 0 1 MPa • z'/ z , • i' 30 s hold • • a • a 3 -. • - * • : • 1 P - , _ • 1 K/S P ToUl • Tjr Total & Tjr 'O'K/S » Tom 3 Tar Tout & Tar ' ^ % _ •o > ra r- o 0 o -• ' DO 30 50 40 20 n __iiver • - . • - • r .1 7/ "• 7 Birch 0 1 • /' // :I'/T l'7 1 MPa. : 1 0 S hnld i 1 K/i 10V 1 I ... * • -I 3 • . • Totai Tar Total & Tar ' Total Tar Total & Tar • i 400 500 600 700 300 900 Temperature, C Figure 5 Evaluation of bio-FC with the weight loss and tar yields from devolatilization of bagasse (top) and silver birch bottom; 'or 1 and 1000 K/s at atmosphenc pressure 'ecor.ed by Fraga et ai (1991). predicted PVM to the reported value. The specific adjustments were selected to exhibit the same qualitative tendencies for higher degrees of mineral catalysis as seen in \ik-Azar's dataset (1997), m which the cation loadings in ceecn were ^aned systematically This procedure shifts gas 'ormation to lower temperatures, while leaving the temperature range for tar release unchanged. The ultimate tar yields are suppressed by ash catalysis, whereas the weight IOSS is reduced by a much smaller factor. "he entire prediction scheme for biomass is evaluated in Fig 5 'or atmosphenc devolatilization, and in Fig. 6 for pressunzed applications, in these cases our full procedure was applied without parameter adjustments and the predicted tar yields, in particular, are accurate indications of the quantitative accuracy of bio-FC at this point in its development. The only sample-specific input were the proximate and ultimate analyses of the whole biomass samples in Fig. 5, the evaluations demonstrate that bio-FC s able to reproduce the much smaller yield enhancements for rapid heating with biomass, compared to coal devolatilization behavior Moreover, the model predicts weight ioss and tar yields from both bagasse and silver birch withm useful quantitative tolerances for all temperatures above 500 3 C At lower temperatures, the model so - 60 - _ 4 0 - 20 -I • otaij Eucalyptus. 10 K/s. 450 C. 300 s 0 2 4 5 3 Pressure, MPa Figure 6. Evaluation of the predicted weight ioss and tar yields from eucalyptus waste for devolatilization at 10 'C/s to 450 °C for 300 s at various pressures, reported by Pmdona etal. (1997) underpredicts observed yields from both biomass 'orms which is probably an indication that the ultimate baseline values for the reaction rate parameters for both components have not yet been specified. In Fig. 6 the predictions are evaluated with data 'or slow pyrolysis at 450 °C for pressures from 0 1 to 7 MPa. Bio-FC correctly predicts that tar release is suppressed at elevated pressures, and that the reduction in weight loss is partially compensated for by higher gas yields. Both predictions at 0.1 M P a are within expenmental uncertainty, as are weight loss levels for all pressures. But the predicted tar yields exceed the measured values at intermediate pressures DISCUSSION Rapid fuel devolatilization generates the gaseous fuels that ignite and stabilize suspension fired flames, and voiatiies account for as much as half the total heat release m full-scale utility boilers plus most of the noxious gases Utility operators currently face a daunting selection of opportunity fuels, including coal, biomass. petroleum cokes, and wastes Test burns and drop-tube testing are established -neans to charactenze just about any solid fossil fuel that can pe pulverized. But physical tests are expensive arc I - e consuming because they involve specialized personnel This paper demonstrates that it is currently possible to predict the devolatilization behavior of coals petroieur cokes, and various forms of biomass within „sef~ quantitative tolerances. The only sample-specie ncut requirements are the proximate and ultimate araivses Provided that an accurate thermal history can pe ass.grec for the process under consideration, F L A S H C H A I N ' - are bio-FC can predict the complete distnbution ot devolatilization products for any of these fue's at any operating conditions. Each simulation takes less than ' ] s on m o d e m personal microcomputers. This paper also introduces a phenome-c eg ca mechanism that transforms predicted pnmar< :'oc-ct distnbutions into the fuel mixtures that actual :-'- ~ pulverized fuel flames. The proposed mecnan s - '-• secondary pyrolysis transforms the primary products ": soot, CH4, C2Hj, H C N , H2S, H 20. H:, C O and C 0 2 : :ec :s all the major tendencies among the levels :' a-z~y : hydrocarbons, oxygenated gas speces. and H 2 as ': > s (1) The sum of the yields of tars, oils, and s o c -e-a-s nearly invanant; (2) The yields of C 0 2 anc -:_ s:a • |